arXiv subjects

Ricardo Gafeira

Publications and source records attributed to Ricardo Gafeira.

14 recordsLinked to original sources

arXiv2026

Modelling solar radial velocities and photometric variability with SOAPv4

Stellar activity remains one of the main limitations in the detection of Earth-like planets using radial velocity (RV) measurements. The Sun, as the only star for which surface features can be spatially resolved, offers a unique testbed for studying the impact of active regions on RV and photometric variability. Using SOAPv4, we modelled solar RV and photometric variability induced by spots and faculae over long timescales. Our goal is to verify whether present-day, state-of-the-art models of the cross-correlation function correctly reproduce the observed variability. Moreover, we aim to assess how the choice of input data and identification technique influences the agreement between simulated and observed signals. To simulate solar RV and photometric time series, we first identified active regions in SDO images. This was done using mathematical morphological (MM) transforms applied to SDO/HMI and AIA images. MM identification was validated against other state-of-the-art identification methods. Using these inputs, we ran SOAPv4 to simulate solar RVs and photometry, and we validated the results with HARPS-N RV observations, as well as with VIRGO/SPM photometric measurements. The simulations that use MM identification achieved the best match with the observed RV time series, yielding residuals with a measured standard deviation of ~0.91 m/s. Other state-of-the-art methods produced higher filling factors and, consequently, larger discrepancies. The photometric simulations reproduced the overall variability trends. We demonstrate that MM transforms accurately identify solar active regions. Using these inputs, SOAPv4 reproduces the observed solar RV variability with a measured standard deviation of the residuals of ~0.91 m/s. Photometric simulations capture the overall variability trends, confirming that SOAP can reliably model the impact of both spots and faculae on solar RVs and photometry.

astro-ph.EP↗

arXiv2025

PoET: the Paranal solar ESPRESSO Telescope

The detection and characterisation of other "Earths", orbiting other suns, is a bold objective of present-day astrophysics. However, this quest is severely challenged by astrophysical "noise" from the host stars, whose signatures distort the observed spectra. Motivated by this problem, we are building a dedicated facility, the Paranal solar ESPRESSO Telescope (PoET). PoET will collect solar light and channel it into the ESPRESSO spectrograph, allowing us to use the Sun as a proxy to unambiguously identify and understand the sources of relevant variability in solar-type stars.

astro-ph.SR↗

arXiv2024

The Sun at millimeter wavelengths V. Magnetohydrodynamic waves in a fibrillar structure

Magnetohydrodynamic (MHD) waves, playing a crucial role in transporting energy through the solar atmosphere, manifest in various chromospheric structures. Here, we investigated MHD waves in a long-lasting dark fibril using high-temporal-resolution (2~s cadence) Atacama Large Millimeter/submillimeter Array (ALMA) observations in Band 6 (centered at 1.25~mm). We detected oscillations in brightness temperature, horizontal displacement, and width at multiple locations along the fibril, with median periods and standard deviations of $240\pm114$~s, $225\pm102$~s, and $272\pm118$~s, respectively. Wavelet analysis revealed a combination of standing and propagating waves, suggesting the presence of both MHD kink and sausage modes. Less dominant than standing waves, oppositely propagating waves exhibit phase speeds (median and standard deviation of distributions) of $74\pm204$~km/s, $52\pm197$~km/s, and $28\pm254$~km/s for the three observables, respectively. This work demonstrates ALMA's capability to effectively sample dynamic fibrillar structures, despite previous doubts, and provides valuable insights into wave dynamics in the upper chromosphere.

astro-ph.SR↗

arXiv2023

The Automatic Identification and Tracking of Coronal Flux Ropes -- Part II: New Mathematical Morphology-based Flux Rope Extraction Method and Deflection Analysis

We present a magnetic flux rope (FR) extraction tool for solar coronal magnetic field modelling data, which builds upon the methodology from Wagner et al. (2023). We apply the scheme to magnetic field simulations of active regions AR12473 and AR11176. We compare the method to its predecessor and study the 3D movement of the newly extracted FRs up to heights of 200 and 300 Mm, respectively. The extraction method is based on the twist parameter and a variety of mathematical morphology algorithms, including the opening transform and the morphological gradient. We highlight the differences between the methods by investigating the circularity of the FRs in the plane we extract from. The simulations for the active regions are carried out with a time-dependent data-driven magnetofrictional model (TMFM; Pomoell et al. (2019)). We investigate the FR trajectories by tracking their apex throughout the full simulation time span. We demonstrate that this upgraded methodology provides the user with more tools and less a-priori assumptions about the FR shape that, in turn, leads to a more accurate set of field lines. The propagation analysis yields that the erupting FR from AR12473 showcases stronger dynamics than the AR11176 FR and a significant deflection during its ascent through the domain. The AR11176 FR appears more stable, though there still is a notable deflection. This confirms that at these low coronal heights, FRs do undergo significant changes in the direction of their propagation even for less dynamic cases. The modelling results are also verified with observations, with AR12473 being indeed dynamic and eruptive, while AR11176 only features an eruption outside of our simulation time window.

astro-ph.SR↗

arXiv2023

Analysis of full-disc H alpha observations: Carrington maps and filament properties in 1909-2022

Full disc observations of the Sun in the H$α$ line provide information about the solar chromosphere and in particular about the filaments, which are dark and elongated features that lie along magnetic field polarity inversion lines. This makes them important for studies of solar magnetism. Since full disc H$α$ observations have been performed at various sites since 1800s, with regular photographic data having started in the beginning of the 20th century, they are an invaluable source of information on past solar magnetism. In this work we aimed at deriving accurate information about filaments from historical and modern full disc H$α$ observations. We have consistently processed observations from 15 H$α$ archives spanning 1909-2022. Our data processing includes photometric calibration of the data stored on photographic plates. We have constructed also Carrington maps from the calibrated H$α$ images. We find that filament areas are affected by the bandwidth of the observation. Thus, cross-calibration of the filament areas derived from different archives is needed. We have produced a composite of filament areas from individual archives by scaling all of them to the Meudon series. Our composite butterfly diagram shows very distinctly the common features of filament evolution, that is the poleward migration as well as a decrease in the mean latitude of filaments as the cycle progresses. We also find that during activity maxima, filaments on average cover about 1% of the solar surface. We see only a weak change in the amplitude of cycles in filament areas, in contrast to sunspot and plage areas. Analysis of H$α$ data for archives with contemporaneous Ca II K observations allowed us to identify and verify archive inconsistencies, which will also have implications for reconstructions of past solar magnetism and irradiance from Ca II K data.

astro-ph.SR↗

arXiv2023

Total electron content PCA-NN model for middle latitudes

A regression-based model was previously developed to forecast the total electron content (TEC) at middle latitudes. We present a more sophisticated model using neural networks (NN) instead of linear regression. This regional model prototype simulates and forecasts TEC variations in relation to space weather conditions. The development of a prototype consisted of the selection of the best set of predictors, NN architecture and the length of the input series. Tests made using the data from December 2014 to June 2018 show that the PCA-NN model based on a simple feed-forward NN with a very limited number (up to 6) of space weather predictors performs better than the PCA-MRM model that uses up to 27 space weather predictors. The prototype is developed on a TEC series obtained from a GNSS receiver at Lisbon airport and tested on TEC series from three other locations at middle altitudes of the Eastern North Atlantic. Conclusions on the dependence of the forecast quality on longitude and latitude are made.

physics.ao-ph↗

arXiv2023

Exploring magnetic loops and serpentine fields in the quiet Sun with the GRIS-IFU

Synthetic observations produced from radiative magnetohydronamic simulations have predicted that higher polarization fractions in the quiet solar photosphere would be revealed by increasing the total integration time of observations at GREGOR resolutions. We present recently acquired disk centre observations of the Fe I $15648.5$ $\mathrmÅ$ line obtained with the GREGOR telescope equipped with the GRIS-IFU during excellent seeing conditions, showing exceptionally high polarization fractions. Our observation reveal an internetwork region with a majority ($>60\%$) of magnetised pixels displaying a clear transverse component of the magnetic field. This result is in stark contrast to previous disk-centre GRIS-IFU observations in this spectral line, which had predominantly vertical magnetic fields in the deep photosphere. At the same time, the median magnetic field strength is weaker than previous GRIS-IFU observations, indicating that the larger fraction of polarization signals cannot be explained by a more active target. We use the Stokes Inversion based on Response functions (SIR) code to analyse the data, performing over $45$ million inversions, and interrogate the impact of two conflicting approaches to the treatment of noise on the retrieval of the magnetic inclination and azimuth. We present several case studies of the zoo of magnetic features present in these data, including small-scale magnetic loops that seem to be embedded in a sea of magnetism, and serpentine fields, focusing on regions where full-vector spectropolarimetry has been achieved. We also present a new open-source Python 3 analysis tool, SIR Explorer (SIRE), that we use to examine the dynamics of these small-scale magnetic features.

astro-ph.SR↗

arXiv2021

Testing the accuracy of Coimbra Astronomical Observatory solar filament historical series (1929-1941)

The present work aims to validate the positions of solar filaments published in the Annals of Coimbra University Astronomical Observatory, currently the Geophysical and Astronomical Observatory of the University of Coimbra, corresponding to years 1929 to 1941. The published Stonyhurst positions were obtained by an original method devised in the early 20th century that used a spherical calculator instrument, a wood-made model of the sun. We used the digital images of the original spectroheliograms to measure the positions of the filaments, and heliographic coordinates were determinate with the routines implemented on python package Sunpy. The correlation coefficients between both sets of coordinates are positive and highly significant. The results validate the method used at the Coimbra observatory and the data published. We conclude that Coimbra solar filaments catalogues are reliable and can therefore be considered for future solar activity studies.

astro-ph.SR↗

arXiv2021

Revisiting the mass- and radius-luminosity relations for FGK main-sequence stars

Scaling relations are very useful tools for estimating unknown stellar quantities. Within this framework, eclipsing binaries are ideal for this goal because their mass and radius are known with a very good level of accuracy, leading to improved constraints on the models. We aim to provide empirical relations for the mass and radius as function of luminosity, metallicity, and age. We investigate, in particular, the impact of metallicity and age on those relations. We used a multi-dimensional fit approach based on the data from DEBCat, an updated catalogue of eclipsing binary observations such as mass, radius, luminosity, effective temperature, gravity, and metallicity. We used the {PARAM web interface for the Bayesian estimation of stellar parameters, along with} the stellar evolutionary code MESA to estimate the binary age, assuming a coeval hypothesis for both members. We derived the mass and radius-luminosity-metallicity-age relations using 56 stars, {with metallicity and mass in the range -0.34<[Fe/H]<0.27 and 0.66<M/M{_\odot}<1.8}. With that, the observed mass and radius are reproduced with an accuracy of 3.5% and 5.9%, respectively, which is consistent with the other results in literature. We conclude that including the age in such relations increases the quality of the fit, particularly in terms of the mass, as compared to the radius. On the other hand, as other authors have noted, we observed an higher dispersion on the mass relation than in that of the radius. We propose that this is due to a stellar age effect.

astro-ph.SR↗

arXiv2021

3D solar coronal loop reconstructions with machine learning

The magnetic field plays an essential role in the initiation and evolution of different solar phenomena in the corona. The structure and evolution of the 3D coronal magnetic field are still not very well known. A way to get the 3D structure of the coronal magnetic field is by performing magnetic field extrapolations from the photosphere to the corona. In previous work, it was shown that by prescribing the 3D reconstructed loops' geometry, the magnetic field extrapolation finds a solution with a better agreement between the modeled field and the reconstructed loops. Also, it improves the quality of the field extrapolation. Stereoscopy represents the classical method for performing 3D coronal loop reconstruction. It uses at least two view directions. When only one vantage point of the coronal loops is available, other 3D reconstruction methods must be applied. Within this work, we present a method for the 3D loop reconstruction based on machine learning. Our purpose for developing this method is to use as many observed coronal loops in space and time for the modeling of the coronal magnetic field. Our results show that we can build machine learning models that can retrieve 3D loops based only on their projection information. In the end, the neural network model will be able to use only 2D information of the coronal loops, identified, traced and extracted from the EUV images, for the calculation of their 3D geometry.

astro-ph.SR↗

arXiv2020

Mimicking spectropolarimetric inversions using convolutional neural networks

Interpreting spectropolarimetric observations of the solar atmosphere takes much longer than the acquiring the data. The most important reason for this is that the model fitting, or "inversion", used to infer physical quantities from the observations is extremely slow, because the underlying models are numerically demanding. We aim to improve the speed of the inference by using a neural network that relates input polarized spectra to the output physical parameters. We first select a subset of the data to be interpreted and infer physical quantities from corresponding spectra using a standard minimization-based inversion code. Taking these results as reliable and representative of the whole data set, we train a convolutional neural network to connect the input polarized spectra to the output physical parameters (nodes, in context of spectropolarimetric inversion). We then apply the neural network to the various other data, previously unseen to the network. As a check, we apply the referent inversion code to the unseen data and compare the fit quality and the maps of the inferred parameters between the two inversions. The physical parameters inferred by the neural network show excellent agreement with the results from the inversion, and are obtained in a factor of $10^5$ less time. Additionally, substituting the results of the neural network back in the forward model, shows excellent agreement between inferred and original spectra. The method we present here is very simple for implementation and extremely fast. It only requires a training data set, which can be obtained by inverting a representative subset of the observed data. Applying these (and similar) machine learning techniques will yield orders of magnitude acceleration in the routine interpretation of spectropolarimetric data.

astro-ph.SR↗

arXiv2020

Analysis of full disc Ca II K spectroheliograms III. Plage area composite series covering 1892-2019

We derive the plage area evolution over the last 12 solar cycles employing data from all Ca II K archives available publicly in digital form known to us, including several as yet unexplored Ca II K archives. We analyse more than 290,000 full-disc Ca II K observations from 43 datasets spanning the period 1892-2019. All images were consistently processed with an automatic procedure that performs the photometric calibration (if needed) and the limb-darkening compensation. The processing also accounts for artefacts plaguing many of the images, including some very specific artefacts such as bright arcs found in Kyoto and Yerkes data. We have produced a plage area time-series from each analysed dataset. We found that the differences between the plage areas derived from individual archives are mainly due to the differences in the central wavelength and the bandpass used to acquire the data at the various sites. We have empirically cross-calibrated and combined the results obtained from each dataset to produce a composite series of plage areas. "Backbone" series are used to bridge all the series together. We have also shown that the selection of the backbone series has little effect on the final plage area composite. We have quantified the uncertainty of determining the plage areas with our processing due to shifts in the central wavelength and found it to be less than 0.01 in fraction of the solar disc for the average conditions found on historical data. We also found the variable seeing conditions during the observations to slightly increase the plage areas during activity maxima. We provide the so far most complete time series of plage areas based on corrected and calibrated historical and modern Ca II K images. Consistent plage areas are now available on 88% of all days from 1892 onwards and on 98% from 1907 onwards.

astro-ph.SR↗

arXiv2012

The Bimodal Colors of Centaurs and Small Kuiper Belt Objects

Ever since the very first photometric studies of Centaurs and Kuiper Belt Objects (KBOs) their visible color distribution has been controversial. That controversy gave rise to a prolific debate on the origin of the surface colors of these distant icy objects of the Solar System. Two different views attempt to interpret and explain the large variability of colors, hence surface composition. Are the colors mainly primordial and directly related to the formation region, or are they the result of surface evolution processes? To date, no mechanism has been found that successfully explains why Centaurs, which are escapees from the Kuiper Belt, exhibit two distinct color groups, whereas KBOs do not. In this letter, we readdress this issue using a carefully compiled set of B-R colors and H(α) magnitudes (as proxy for size) for 253 objects, including data for 10 new small objects. We find that the bimodal behavior seen among Centaurs is a size related phenomenon, common to both Centaurs and small KBOs, i.e. independent of dynamical classification. Further, we find that large KBOs also exhibit a bimodal behavior of surface colors, albeit distinct from the small objects and strongly dependent on the `Haumea collisional family' objects. When plotted in B-R, H(α) space, the colors of Centaurs and KBOs display a peculiar N shape.

astro-ph.EP↗

arXiv2012

Mass-luminosity relation for FGK main sequence stars: metallicity and age contributions

The stellar mass-luminosity relation (MLR) is one of the most famous empirical "laws", discovered in the beginning of the 20th century. MLR is still used to estimate stellar masses for nearby stars, particularly for those that are not binary systems, hence the mass cannot be derived directly from the observations. It's well known that the MLR has a statistical dispersion which cannot be explained exclusively due to the observational errors in luminosity (or mass). It is an intrinsic dispersion caused by the differences in age and chemical composition from star to star. In this work we discuss the impact of age and metallicity on the MLR. Using the recent data on mass, luminosity, metallicity, and age for 26 FGK stars (all members of binary systems, with observational mass-errors <= 3%), including the Sun, we derive the MLR taking into account, separately, mass-luminosity, mass-luminosity-metallicity, and mass-luminosity-metallicity-age. Our results show that the inclusion of age and metallicity in the MLR, for FGK stars, improves the individual mass estimation by 5% to 15%.

astro-ph.SR↗